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Multi-muscle MRI Texture Analysis for Therapy Evaluation in Duchenne Muscular Dystrophy

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Computer Information Systems and Industrial Management (CISIM 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11703))

Abstract

The study presents a strategy for indicating the textural features that are the most appropriate for therapy evaluation in Duchenne Muscular Dystrophy (DMD). The strategy is based on “multi-muscle” texture analysis (simultaneously processing several distinct muscles) and involves applying statistical tests to pre-eliminate features that may possibly evolve along with the individual’s growth. The remaining features, considered as age-independent, are ranked using the Monte Carlo selection procedure, from the most to the least useful in identifying dystrophy phase. In total 124 features obtained with six texture analysis methods are investigated. Various subsets of the top-ranked age-independent features are assessed by six classifiers. Three binary differentiation problems are posed: the first vs. the second, the second vs. the third, and the first vs. the third dystrophy phase. The best vectors of age-independent features provide a classification accuracy of 100.0%, 86.9%, and 100.0%, respectively, and comprise 16, 12, and 9 features, respectively.

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Acknowledgments

I would like to thank Noura Azzabou from the Institute of Myology, NMR Laboratory, Paris, France for providing the database of images and ROIs on which the experiments were performed in this study. I also thank the participants of the COST Action BM1304, MYO-MRI for valuable discussions.

This work was supported by grant S/WI/2/18 (from the Bialystok University of Technology), founded by the Polish Ministry of Science and Higher Education.

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Authors and Affiliations

  1. Faculty of Computer Science, Bialystok University of Technology, Bialystok, Poland

    Dorota Duda

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  1. Dorota Duda
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Correspondence to Dorota Duda .

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Editors and Affiliations

  1. Bialystok University of Technology, Bialystok, Poland

    Khalid Saeed

  2. University of Calcutta, Calcutta, India

    Rituparna Chaki

  3. Mihajlo Pupin Institute, Belgrade, Serbia

    Valentina Janev

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Duda, D. (2019). Multi-muscle MRI Texture Analysis for Therapy Evaluation in Duchenne Muscular Dystrophy. In: Saeed, K., Chaki, R., Janev, V. (eds) Computer Information Systems and Industrial Management. CISIM 2019. Lecture Notes in Computer Science(), vol 11703. Springer, Cham. https://doi.org/10.1007/978-3-030-28957-7_2

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  • DOI: https://doi.org/10.1007/978-3-030-28957-7_2

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-030-28957-7

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